• 제목/요약/키워드: 비모수통계방법

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Comparison of Some Nonparametric Statistical Inference for Logit Model (로짓모형의 비모수적 추론의 비교)

  • 정형철;김대학
    • The Korean Journal of Applied Statistics
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    • v.15 no.2
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    • pp.355-366
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    • 2002
  • Nonparametric statistical inference for the parameter of logit model were examined. Usually nonparametric approach is milder than parametric approach based on normal theory assumption. We compared the two nonparametric methods for legit model, the bootstrap and random permutation in the sense of coverage probability. Monte Carlo simulation is conducted for small sample cases. Empirical power of hypothesis test and coverage probability for confidence interval estimation were presented for simple and multiple legit model respectively. An example were also introduced.

Reliability Analysis Using Parametric and Nonparametric Input Modeling Methods (모수적·비모수적 입력모델링 기법을 이용한 신뢰성 해석)

  • Kang, Young-Jin;Hong, Jimin;Lim, O-Kaung;Noh, Yoojeong
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.30 no.1
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    • pp.87-94
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    • 2017
  • Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.

반복이 없는 이원배치에서 분포의 동일성 검정에 대한 비모수적 검정법

  • 이기훈
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.765-774
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    • 1997
  • 본 논문에서는 반복이 없는 이원배치에서 교호작용의 존재를 가정하고 처리수준간의 모집단 분포의 동일성을 검정하는 비모수적 검정법을 제안하였다. 검정통계량의 구성을 위하여 순위벡터를 그 구조의 형태별로 정리한 순위위치벡터를 제안하고, 이의 특성과 응용가능성을 연구하였다. 또한 모의 검정력 연구를 통하여 기존의 비모수적 방법이 갖는 약점과 제안한 통계량의 우수함을 실증하였다.

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비모수 퍼지회귀모형

  • Choe, Seung-Hoe;Kim, Hae-Gyeong;Seong, Na-Yeong
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.199-201
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    • 2003
  • 본 연구에서는 크리스프자료(crisp data)인 독립변수와 퍼지자료(fuzzy data)인 종속변수 사이의 관계가 특정한 함수로 표현되지 않는 비모수 퍼지회귀모형을 분석하기위하여 퍼지수 순위와 퍼지순위변환방법을 소개하고, 모의실험을 통하여 퍼지순위변환방법의 효율성을 조사한다.

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Comparison of estimation methods for expectile regression (평률 회귀분석을 위한 추정 방법의 비교)

  • Kim, Jong Min;Kang, Kee-Hoon
    • The Korean Journal of Applied Statistics
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    • v.31 no.3
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    • pp.343-352
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    • 2018
  • We can use quantile regression and expectile regression analysis to estimate trends in extreme regions as well as the average trends of response variables in given explanatory variables. In this paper, we compare the performance between the parametric and nonparametric methods for expectile regression. We introduce each estimation method and analyze through various simulations and the application to real data. The nonparametric model showed better results if the model is complex and difficult to deduce the relationship between variables. The use of nonparametric methods can be recommended in terms of the difficulty of assuming a parametric model in expectile regression.

베이지안 방법에 의한 K개 지수분포 모수들의 기하평균 추정에 관한 연구

  • Kim, Dae-Hwang;Kim, Hye-Jung
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.169-174
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    • 2002
  • 본 연구는 k개 지수분포 모수들의 기하평균에 대한 베이지안추정 방법을 제시하였다. 이를 위해 Tibshirani가 제안한 직교변환법으로 비정보적 사전확률분포를 도출하여 모수들의 결합사후확률분포를 유도해 내었으며, 이 분포 하에서 가중 몬테칼로 방법을 사용하여 기하평균을 추정하는 절차를 제안하였다. 모의실험과 실제자료의 예를 통해 제안된 베이지안 추정의 유효성 및 효용성을 보였으며, 본 연구에서 제안한 사전확률분포가 전통적인 포함확률을 기준으로 볼 때, Jeffrey의 사전확률분포 보다 더 유효한 추정을 함을 보였다.

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Nonparametric procedures using aligned method and joint placement in randomized block design with replications (반복이 있는 랜덤화 블록 계획법에서 정렬방법과 결합위치를 이용한 비모수 검정법)

  • Lee, Eunjee;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.291-299
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    • 2017
  • Mack and Skillings (1980) proposed nonparametric procedures in a randomized block design with replications as general alternatives. This method is used to find the difference in the treatment effect; however, it can cause a loss of inter block information using the ranking in each block. In this paper, we proposed new nonparametric procedures in a randomized block design with replications using an aligned method proposed by Hodges and Lehmann (1962) that used information of blocks and based on the joint placement suggest by Chung and Kim (2008). We also compared the power of the test of the proposed procedures and established a method through Monte Carlo simulation.

Nonparametric method using aligned method and linear placement statistics in randomized block design with replications (반복이 있는 랜덤화블록 모형에서 정렬방법과 선형위치통계량을 이용한 비모수 검정법)

  • Jeon, Soyoung;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.281-290
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    • 2017
  • Mack and Skillings (1980) proposed a nonparametric method in a randomized block design with replications. This method employs the mean of observations instead of each observation. However, it has the inherent disadvantage that there may be a loss of information. In this paper, we proposed a nonparametric method that employees an aligned method and linear placement statistics to supplement its weakness. A Monte-Carlo study is performed to compare the power of the proposed method with previous methods.

비모수 회귀모형의 차분에 기저한 분산의 추정에 대한 고찰

  • 김종태
    • Communications for Statistical Applications and Methods
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    • v.5 no.1
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    • pp.121-131
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    • 1998
  • 이 논문의 목적은 비모수 회귀모형에 있어서의 오차의 분산을 추정하는 방법들 중 차분에 기저한 방법 (difference-based methods)을 이용한 기존의 추정량들을 비교 분석하는데 있다. 특히 점근적인 최적 이차 차분에 기저한 Hall과 Kay, Titterington(1990)의 HKT 추정량에 대한 그들의 추정량에 대한 문제점들을 제시하고, HKT추정량과, GSJS추정량, Rice추정량에 대하여 모의 실험을 이용하여 모수에 대한 수렴 속도를 비교 분석 하였다. 또한 GSJS 추정량에 대한 일치성과 수렴 속도를 보였다.

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Non-Inferiority Test in a Two-Arm Trial and a Three-Arm Trial Including a Placebo (활성대조군을 이용한 두 군 설계와 위약군을 포함한 세 군 설계의 비열등성 시험)

  • Lee, Ji-Sun;Kim, Dong-Jae
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.947-957
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    • 2008
  • Two-arm non-inferiority trials is often applied to parametric procedure suggested by Hauschke et al. (1999). Since this design does not allow a direct comparison of a new treatment group with placebo group, parametric procedure in a three-arm non-inferiority trial with a placebo group was suggested by Pigeot et al. (2003). But, procedures in these designs are necessary for distribution assumptions. Therefore we propose, in this paper, non parametric procedures employing Wilcoxon rank sum test in a two-arm design and linear contrast test suggested by Scheirer et al. (1976) in a three-arm design. The proposed nonparametric procedures and parametric procedures are compared by Monte Carlo simulation study.